DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Kanghak | ko |
dc.contributor.author | Lee, Sunho | ko |
dc.contributor.author | Son, Jeonghoon | ko |
dc.contributor.author | Cha, Meeyoung | ko |
dc.date.accessioned | 2023-10-18T06:01:54Z | - |
dc.date.available | 2023-10-18T06:01:54Z | - |
dc.date.created | 2023-10-18 | - |
dc.date.issued | 2014-04 | - |
dc.identifier.citation | 23rd International Conference on World Wide Web, WWW 2014, pp.319 - 320 | - |
dc.identifier.uri | http://hdl.handle.net/10203/313509 | - |
dc.description.abstract | Question & Answer (Q&A) behaviors on social media have huge potential as a rich source of information and knowledge online. However, little is known about how much diversity there exists in the topics covered in such Q&As and whether unstructured social media data can be made searchable. This paper seeks the feasibility of utilizing social media data for developing a Q&A service by examining the topic coverage in Twitter conversations. We propose a new framework to automatically extract informative Q&A content using machine learning techniques. | - |
dc.language | English | - |
dc.publisher | International World Wide Web Conference Committee | - |
dc.title | Finding informative Q&As on twitter | - |
dc.type | Conference | - |
dc.identifier.wosid | 000455947000002 | - |
dc.identifier.scopusid | 2-s2.0-84990982188 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 319 | - |
dc.citation.endingpage | 320 | - |
dc.citation.publicationname | 23rd International Conference on World Wide Web, WWW 2014 | - |
dc.identifier.conferencecountry | KO | - |
dc.identifier.conferencelocation | Seoul | - |
dc.identifier.doi | 10.1145/2567948.2577291 | - |
dc.contributor.localauthor | Cha, Meeyoung | - |
dc.contributor.nonIdAuthor | Kim, Kanghak | - |
dc.contributor.nonIdAuthor | Lee, Sunho | - |
dc.contributor.nonIdAuthor | Son, Jeonghoon | - |
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